THE COMBINATION OF GEOMATIC APPROACHES AND OPERATIONAL

MODAL ANALYSIS TO IMPROVE CALIBRATION OF FINITE ELEMENT

MODELS: A CASE OF STUDY IN SAINT TORCATO CHURCH (GUIMARÃES,

PORTUGAL).

Luis Javier Sánchez-Aparicio1*

, Belén Riveiro2, Diego Gonzalez-Aguilera

1, Luís F. Ramos

3

1Department of Land and Cartographic Engineering. University of Salamanca,

High Polytechnic School of Avila, Hornos Caleros, 50, 05003, Avila (Spain)

Tlf: +34 920353500; Fax: +34 920353501

2Department of Material Engineering, Applied Mechanics and Construction.

School of Industrial Engineering. University of Vigo. Vigo, (Spain)

Tel.:+34 986 813 661; fax:+34 986 811 924.

3ISISE, Departament of Civil Engineering, University of Minho, Guimarães (Portugal)

Tlf: +351 253510200; Fax: +351 253510217; lramos@civil.uminho.pt

*Corresponding author: Tel.:+34 920353500; ; fax:+34 920353501

E-mail address: luisj@usal.es

Abstract

This paper present a set of procedures based on laser scanning, photogrammetry (Structure

from Motion) and operational modal analysis in order to obtain accurate numeric models which

allows identigying architectural complications that arise in historical buildings. In addition, the

method includes tools that facilitate building-damage monitoring tasks. All of these aimed to

obtain robust basis for numerical analysis of the actual behavior and monitoring task.

This case study seeks to validate said methodologies, using as an example the case of Saint

Torcato Church, located in Guimãres, Portugal.

Abbreviations: UAV, Unmanned Aerial Vehicle; SfM, Structure from Motion PW,

Photogrammetry Workbench; MAC, Modal Assurance Criterion; DR Douglas-Reid Method,

ICP Iterative Closest Point; NURBS Non-Uniform Rational B-Splines.

Keywords: Structure from motion; Laser scanner surveying; Finite Element Model; Modal

updating; Masonry structures; Orthoimage; Damage Survey; CAD modelling.

1. Introduction

The conservation of historic buildings requires understanding their structural behaviour, and

consequently: (i) Their boundary conditions, (ii) The characteristics of the constitutive materials

(iii) The origin of the damage that the building suffers and (iv) Their vulnerability [1]. Therefore

the creation of accurate numerical models is imperative in order to obtain adequate restoration

systems.

Masonry walls are very common in the vast majority of existing monuments. Cracked elements,

associated with different events (settlements and/or excessive displacement loadings) are a

common problem that reduces the service life of these structures [2]. The fracture phenomena

(cracks) are caused by the masonry’s high brittleness to tensile stresses. Furthermore, the

structural behaviour is highly dependent of the structural geometry. This is why four conditions

are required to carried out proper analysis: (i) Having a complete and accurate geometric

characterization of the structure; (ii) Knowing the material´s mechanical properties (iii)

Characterizing all the loads acting in the structure; and (iv) Providing numerical models that

correctly simulate the characteristic behaviour of the structure (non-linear material behaviour,

ground settlement, contact between bricks, etc.).

Modern restoration techniques for built heritage are characterized by minimal intervention,

compatibility, durability and reversibility [3]. Identifying and to monitoring the pathological

condition of the building plays a key role in understanding the current behaviour of the structure

and the choice of restoration methods to be accomplished [4].

Traditional measuring methods often had a significant dependence of the worker’s skills and

they normally have associated high time cost. These methods were replaced by direct

interpretations done over the building plans (design models) [5-7]. The constant progress of the

numeric method of finite elements and computer processing allows the generation of

increasingly complex geometric models; that is why it is more and more imperative the

necessity of relying on sensors capable to provide massive detailed data and features for the

model. Is in this field where geomatic sensors like terrestrial laser scanner [8, 9] or digital

camera [10] have acquired important roles, due to the capacity of acquire accurate geometrical

information needed by the numerical models.

In the present paper, the proposed methodology for data acquisition combines and enhances the

laser scanning and digital camera system providing, beside the characteristics defined above, the

versatility of adaptation to different infrastructures. All of this within a single application, a

hybrid point-cloud, which greatly eases the preparation of geometrically precise numerical

models that also serve as a basis for the monitoring of the structure through the analysis of,

either the point-cloud or by the analysis of the obtained orthoimages.

The paper relies on the application of the proposed methodology on a case study, St. Torcato

Church, close to the city of Guimarães, Portugal [1]. This historical construction has moderate

to severe damage and needs to be strengthened. The methodology has been carried out to

upgrade and calibrate the finite element model using a global dynamic identification, including

crack and geometric improvement, in order to complement with the static and dynamic

monitoring system and a future numerical analysis. All this will be made in order to obtain the

current stress state of the building and asses the effectiveness of subsequent restoration

mechanism that aim at stabilizing the damage.

Within this context, this article attempts to demonstrate a methodology for data acquisition and

processing and it is organized in the following way: Section 1 is the introduction; Section 2

presents the instruments for data acquisition which are the laser scanner and the set formed by

the UAV and digital camera; Section 3 wherein the methodology for obtaining the hybrid point-

cloud and the calibration of the model is shown; Section 4 the data obtained by the laser scanner

and the digital camera sensors is analysed separately, for the presented case study and for the

potential of the hybrid point-cloud (this applies not only to the numerical finite-element analysis

but also to damage analysis monitoring); and finally in Section 5, the conclusions are drawn.

2. Materials and methods

As described in Section 1, the aim of this methodology is to generate precise finite-element

numerical models for subsequent structural analysis. These must be precise, in terms of

geometry accuracy and they must contain the necessary data to monitor and track the evolution

of damages in the structure. All this within an accurate georeferenced framework and with non-

intrusive sensors as the main source.

2.1. Laser scanner system: the terrestrial laser scanner

Currently the terrestrial laser scanning system has acquired great relevance by offering a wide

range of advantages; one of the greatest one is the acquisition of non-contact three-dimensional

geometry of the analyzed surface, preventing any disruption and allows to accurately capture

geometry, providing a high density of data (millions of points) [11]. This feature includes that it

does no dependency on specific lighting conditions [12]. It is therefore the combination of

accuracy, speed and range of measures that has placed the system as the most powerful tool for

three-dimensional modeling and reconstruction of monuments [13, 14].

In order to establish a valid methodology to make more accurate finite element models, two

different laser scanning systems have been analyzed based on different measurement principles

(Table 1.): (i) Riegl LMS-Z390i based on time of flight principle (ii) Faro Focus 3D based on

the phase shift principle. For details on these measurement principles, refer to [15].

Riegl LMS Z-390i Faro Focus 3D

Measurement principle Time of flight Phase shift

Wavelength 1550 nm 905 nm

Measurement range 1-400 m 0.6-120 m

Accuracy nominal value

6 mm a 50 m in specific lighting

and reflectance conditions.

2 mm a 25m in specific lighting

and reflectance conditions.

Field of view

3600 horizontal

800 vertical

3600 horizontal

3050 vertical

Capture rate 11000 points/sec 122.000/976.000 points/sec

Beam divergence 0.3 mrad 0.19 mrad

Table 1: Comparison of technical specifications between laser scanner system Rielg LMS Z-

390i and Faro Focus 3D.

2.2. Imaging System: UAV and “Structure from Motion”

While the laser scanning system allows fast capture and processing of data, it has some

drawbacks such as the difficulty for transport and the restriction of stationing in certain elevated

places inside historic buildings, these places often are critical. Therefore, it is necessary to use

additional platforms and sensors capable of providing accurate data from any position; for this

the onboard digital camera on an Unmanned Aerial Vehicle (UAV) platform is used (Fig. 1).

Fig.1. Image of the UAV platform and the digital camera (Left). Image taken during the data

collection of the point cloud SfM (Right).

The chosen photogrammetric platform was designed by Roca et al [16]. It is made of aluminum

and carbon fiber, and comprises a total of eight MK-3638 SLOWFLY APC propeller motors

controlled by a central 12x3.8 Brushless Control V2.0 that can manage separately the rotational

speed of each of the motors. All of this provides the system with great stability and robustness

against failure in flight.

In addition to this platform, a low-cost sensor, a Canon EOS 450D digital camera that had been

previously geometrically calibrated (Table 2), and a Canon EF 20mm wide-angle lens were

assembled. The wide-angle lens is meant to minimize the amount of images taken.

Parameter Value

Sensor size

W= 22.2425mm

H=14.8336mm

Principal point

Xp=10.8716mm

Yp=7.4449mm

Focal length f=20.4222mm

Radial distortion

K1= 2.157 e-004mm

K2= -4.189 e-007mm

K3=0mm

Tangential

distortion

P1= 4.321 e-005mm

P2= -1.003 e-005mm

Table 2: Canon EOS 450D digital camera geometric calibration settings.

In recent years photogrammetric data processing systems (SfM) have taken a great relevance;

they are able to include into their structure the advantages of computer vision (automation and

flexibility) and those of photogrammetry (accuracy and reliability) [17] in order to obtain dense

three-dimensional models (point clouds) that can compete in accuracy with the laser scanner

system [18]. Within this field highlights the Photogrammetry Workbench (PW) software, which

implements the “Structure from Motion” system, ensuring automation (in the transformation of

2-D images to 3-D point clouds), flexibility (by allowing work with any type of camera,

calibrated and non-calibrated) and quality (to ensure precision and quite acceptable resolutions).

3. Methodology

3.1. Generating the CAD model and its integration with finite elements

The early stage in the laser scanning and the Structure from Motion (SfM) data processing, have

been omitted in this article, since our main interest is focused on establishing a robust

methodology that serves as a template for subsequent restoration actions. This template will be

based on the hybrid point cloud, which comes from the combination of data obtained from laser

scanning, the SfM and the analysis of the products that are obtained from them. For more details

about SfM flow see either [19]

Also is imperative to building an accurate CAD model which allow us to evaluate the actual

behavior of the construction as a basis for the numerica analysis. However, at an early stage, the

point cloud provided by the laser scanning and the SfM present superabundant information in

different coordinate systems. As a result, this data is not suitable for CAD model building.

Following a semi-automatic method that allows adapting the point cloud to an accurate and

suitable CAD model for numerical analysis is presented (Fig.2).

This methodology requires a multi-phase post-processing that involves three main steps: (i)

Data fusion at the same coordinate system through registration algorithms; (ii) Point cloud

resampling and (iii) Point cloud simplification (removing certain architectural details without

relevance) and parameterization for CAD model conversion.

Fig. 2 Workflow for the proposed methodology.

3.1.1. Hybrid point cloud registration

A complete documentation of historical buildings requires the use of multiple point cloud data

set. Is a requirement therefore to place all of these point clouds in the same coordinate system in

order to be processed together.

The proposed methodology is based on a registration system coarse to fine. In an initial stage a

point cloud pair-wise registration is carried out. This step takes as a base the ICP (Iterative

Closest Point) algorithm[20], that minimize the difference between two points clouds, requiring

a total of n-1 alignments, where n is the number of point clouds.

Using a pair-wise registration causes an error propagation along the registration of all the point

cloud scans. In order to minimize this error accumulation a global registration, based on

Generalized Procrustes Analysis[21], was used considering the pair-wise registration,

previously made, as the rough registration needed.

3.1.2. Hybrid point cloud resampling and CAD conversion

Traditionally the step procedure from the raw point cloud to the CAD model could be made

through three different approaches [22]: (i) Orthogonal views; (ii) Sections applied along

directions and over the mesh and (iii) Non-Uniform Rational B-Splines(NURBS) generated

from the mesh. The two first approaches require a high manual work made by the user, whereas

the NURBS approach demands high computational cost.

In this article an alternative and semi-automatic approach is presented, which combines NURBS

and parametric shapes approximations with the addition of a segmentation process described

below, in order to build a suitable CAD model for structural applications. While NURBS-based

method was used for complex shapes like (vault or domes), the parametric-based method was

used for the rest of the structure.

Once the registration procedure has been completed, the resulting point cloud needs to be

resampled (due to the high amount of data) in order to generate a suitable CAD model for the

numerical analysis. In this case several methodologies could be applied based on[23]: (i)

Principal Component Analysis; (ii) Quadric-Based Polygonal Surface Simplification; (iii)

Clustering methodologies and (iv) Radial Based Function. For the proposed methodology a

resampling based on curvature has been applied, in order to decimate flat surfaces without

losing detail in features areas. This curvature based resampling follows the next steps: (i)

Creating a local neighborhood of the analysis point; (ii) Local surface based on quadratic

approximation and (iii) Extraction of the normal and principal curvatures.

After that, the resulting point cloud is meshed, since the majority of segmentation procedures

are also performed over meshes. The segmentation process is performed by Functionally

Decomposed Surface Models[24]. Once the segmentation is done, the different surfaces created

are approximate to NURBS and parametric shapes. As a result a manageable CAD model is

generated and could be imported and used for a FEM package.

Additionally to the mentioned above, some relevant features like cracks, can be included into

the CAD model that defines more realistically the building’s behavior. It is sufficient to extract

the area of interest from the point cloud, either SfM or laser, to mesh that area and to

incorporate it into the CAD model (Fig. 2).

Fig. 3 Graphical description of the proposed methodology. From left to right: point cloud, mesh

model, segmentation model, CAD model with major cracks.

3.2. Crack recognition and characterization

Digital image analysis is a tool of great potential in the field of pathological characterization of

buildings. Several authors demonstrate the feasibility of this analysis to characterize either from

the terrestrial laser scanner [25, 26] or from the image captured by a digital camera [27, 28].

Besides offering robust tools for generating three-dimensional models from two-dimensional

data (digital image), PW can also obtain orthoimages on specific areas and specific levels,

providing the user with precise documentation from anywhere in the building.

Given the high density of points gathered during the three-dimensional reconstruction, the

production of orthoimages will require only two points to provide adequate scale, taken from

the laser point cloud and a reference plane, in order to run an orthographic projection. The pixel

size of this projection is calculated according to the density of the cloud of points, close to the

resolution of the initial images [29].

Given the fact that the obtained orthoimage stands as a product without geometric distortions

and in real scale, it is sufficient to directly measure on it and so obtaining crack characterization

(length and opening).

3.3. Finite element numerical model

The geometric accuracy and high level of detail provided by the laser scanning systems and

structure from motion, provide complex CAD models. In order to solve this geometric

complexity, for the discretization elements it is required: (i) high flexibility to adapt themselves

to the geometry and (ii) great compatibility with automatic meshing algorithms [7]. All this

makes the tetrahedral discretization elements with an isoparametric formulation the most

suitable for the meshing of complex CAD models.

3.4. Calibration of the finite element numerical model

The analytical results obtained from the calculation model are sensitive to material properties

and boundary conditions [30] thus making necessary to gather experimental data to optimize the

numerical model.

Among the different possibilities availables today for the implementation of in-situ tests on

historic buildings, experimental modal identification is the most popular method [1]. This

technique is a non-intrusive system with the capability to identify the global properties of the

structure. It allows to obtain vibration frequencies, damping coefficients and mode shape of

historic buildings, which may be related to various physical properties (Young modulus,

density, stiffness of connections between parts, etc.) wich makes possible to validate the

analytical models [31].

This publication builds on the data obtained from the accelerometers configuration adopted in

2009. The campaign counted a total of 35 measuring points with 9 sets spread throughout the

Church, for more details see [1] (Fig. 4).

Fig. 4. Scheme of the arrangement of the 35 accelerometers on the Church (Above). Mode

shape obtained from operational modal analysis (Bellow).

The basic objective of these methods is to improve the correlation between the experimental

data and those obtained from finite element model, through small changes in a group of model

parameters[32]. The criterion often used to assess the correlation is the MAC (Modal Assurance

Criterion), this being defined from the following formula (1)[33]:

𝑀𝐴𝐶𝑢,𝑑 =[(𝜑𝑖

𝑢)𝑇(𝜑𝑖

𝑑)]2

(𝜑𝑖𝑢)

𝑇(𝜑𝑖

𝑢)(𝜑𝑖𝑑)

𝑇(𝜑𝑖

𝑑) (1)

where 𝜑𝑖𝑢 y 𝜑𝑖

𝑑 correspond to the mode shape vector on experimental and numerical model

respectively for a vibration mode i.

As noted above, the goal is to minimize the existing differencies between the experimental

behaviour and numerical model, considering the experimental values as references. Used in

2007 for the calibration of the numerical model for the Monza Cathedral bell tower [34], the

methodology proposed by Douglas-Reid [35] (DR) can be used for calibration of finite element

numerical models. This method tries to minimize the difference between theoretical and

experimental parameters through the natural frequencies, or another modal parameter, using the

following approach:

𝑅𝑖𝐹𝐸(𝑋1, 𝑋2, … , 𝑋𝑛) = ∑ [𝐴𝑖𝑘𝑋𝑘 + 𝐵𝑖𝑘𝑋𝑘

2]𝑁𝑘=1 + 𝐶𝑖 (2)

To solve these equations, a total of 2n+1 values are required to be calculated, taking into

account initial values, as well as lower and upper bounds for all updating parameters.

Using the methodology followed by [34], the next step consists of determing the modal

frequencies and minimize their difference according to the following objective function (3)(4):

𝐽 = ∑ 𝑤є2𝑚𝑖=1 (3)

є = 𝑓𝑖𝐸𝑋𝑃 − 𝑓𝑖

𝐹𝐸(𝑋1, 𝑋2, … , 𝑋𝑛) (4)

where J is the objetive fuction to be minimized, w are the weights considered through

engineering criterion and e represents the error function (difference between the frequency

obtained by operational modal analysis 𝑓𝑖𝑂𝑀𝐴 and numerical analysis𝑓𝑖

𝐹𝐸).

The main drawback of this methodology lies in the consideration of a unique modal parameter;

frequency. To obtain more accurate results the objective function must be modified, including

the MAC values(5):

𝐽 = 1/2 [𝑊𝑓 ∑ (𝑓𝑖,𝐹𝐸𝑀2 −𝑓𝑖,𝐸𝑋𝑃

2

𝑓𝑖,𝐸𝑋𝑃2 )

2𝑚𝑖=1 +𝑊𝑀 ∑ (1 −𝑀𝐴𝐶𝑖,𝐹𝐸𝑀)

2𝑚𝑖=1 ] (5)

where J is the objetive function to be minimized, Wf and Wm are the weights considered for the

frequency and vibration modes, f is the frequency and 𝑀𝐴𝐶 the modal assurance criterion

values, both values corresponding to the vibration mode i.

4. Experimental result and discussion

Located in the village of St. Torcato, within the municipality of Guimarães (northern Portugal),

the Church of St. Torcato is a clear example of historic building built in stone material, showing

moderate-severe structural damage made evident mostly by cracks in its main façade. Starting at

the entrance arch keystone, it extends through the rosette to the coronation, splitting this

element in two macroblocks [1] (Fig. 5).

Such crack increases the width along its development up to the roof. The movement in opposite

directions of the main façade towers due to the settlement suffered by the building is

remarkable, as well as some “chrusing” type cracks caused by the compressive stress

concentration resulting from eccentric loads originating in the towers.

Fig. 5. Representation of the possible structural failure collapse mechanisms of the Church of

Saint Torcato. It is possible to observe the formation of two macro-blocks.

Built in style “Neo-Manuelinio” the Church of Saint Torcato mix Classics, Gothic, Renaissance

and Romanesque elements in its extension [6].This gives it a special and complex aesthetic that

along its length, with a height of about 50 m in the towers, prevents effective tridimensional

data capture with laser scanner, topographic techniques or manual measurements [36]. The

binomial structure from motion and laser scanning is the ideal solution allowing abundant and

accurate three-dimensional data capture anywhere in the building.

The results obtained are hereby analyzed independently, according to the source sensor (laser

scanner or digital camera) and the resulting numerical model of the combination of these and

the calibration using operational modal analysis.

4.1. Terrestrial Laser Scanner

For the study we have considered the two most popular measuring systems for survey of

buildings and civil infrastructures: the laser time of flight and phase difference [25].

Multiple tests have been carried out in the exterior as well as in the interior of the Church. Since

the point-cloud is defined by densisty of points, the acquisition rate and range, the laser scanner

LMS Z-390i Rielg (based on time of flight) is considered to be the most suitable for data

capture in the exterior. Besides, it has a larger range compared to the Faro Focus 3D laser.

Indoors, the data acquisition speed of the Faro Focus 3D scanner (122000 points/sec) compared

to the speed of the Riegl LMS laser Z-390i (11000 points/sec), together with its portability

proved to be the most important advantages for gathering the data in the interior of the Church.

While in both cases the laser system provides a sufficient and suitable density of points to

accurately monitor deformations [37], the amount of data and distinctive features provided

might be insufficient fo the extraction and monitoring of cracks (for example, it does not record

texture) (Fig. 6).

Fig. 6. Settlement of the entrance vault detail (Left). Settlement of the entrance vault detail

(Right).

The final model had a total of 29 scans and 267.601.626 points: (i) 14 scans were done of the

outside with the Riegl LMS laser Z-390i, (ii) 3 interior shots were taken with the Riegl LMS

laser Z-390i and (iii) 12 interior scans were made with the Faro Focus 3D laser. However, the

top of the towers and the rooftop of the Church could not be modelled because no suitable

location was found for the laser to reach those areas. In addition, the data collection was

hampered by additional conditions: the excesive laser beam skew angle on the ledge, top of the

towers an the openings between the chapels preventing a complete and accurate characterization

of the building and of the critical areas. Thus requiring a complementary technique capable of

solving such weaknessess, UAV and SfM.

4.2. UAV and Structure from Motion

The point-clouds collected by laser scanning do not provide a sufficient amount of data for a

full geometric characterization of the outer shell: either the distance from scanner to object the

range is too large, the point of view is insufficient or the laser system cannot be placed in a

certain location, such as in the upper region of the façade beyond the central cornice.

In addition to the aforementioned, the obliqueness phenomenon must be considered. As shown

by authors such as [38, 39], this phenomenon is highly correlated with the value of uncertainty

in obtaining a point’s spatial coordinates. This phenomenon is of great importance in obtaining

accurate products and it is highlighted by this case study, where it is critical in certain areas,

such as in the inclination of the towers or in the cracking of the central façade.

All this requires a supplementary technology to the laser scanning, this is UAV + SfM; a non-

intrusive way of solving the problems described above through its great portability and ability to

collect data. Besides, it gathers an extra supply of analyzable features, which makes it possible

to get complete point-cloud models, which form the foundation for accurate and thorough CAD

models. These models profit from the features obtained from the hybrid point-cloud, such as

cracks (Fig. 7).

Fig. 7. Front elevation of the point cloud obtained through SfM technique and PW software

(Left). Detailed comparison between the laser scanner point cloud and the one obtained in PW

software (Right).

This model, generated through the describend technique, is comprised of a total of 398

photographs taken by UAV platform: (i) 273 photos of the main façade dividen in 3 vertical

strips ( 1 for each tower and one for the main façade) and (ii) 125 photos of the cracks on

chapels, also divided in 3 vertical strips. Alongside these photographs, 117 aditional shots were

taken without UAV platform (terrestrial photogrammetry): (i) 85 photos of the arches of the

chapels of the main nave and (ii) 32 photos at the level of the Church choir.

Both techniques, terrestrial laser scanner and SfM, complement to each other, and their

combination is the ideal solution for restoring built heritage. While the laser scanner provides

the system a set of precise, dense and fast capture data with which it is possible to monitor

structural movement and generate a CAD model suitable for numerical analysis, the UAV+ SfM

system combines with it perfectly supplying the geometric data of the areas that were

unreachable through the previous system. In addition, it characterizes completely the structure’s

pathological conditions by obtaining direct and georeferenced data.

However, the resulting data of both sensor show different coordinate system but the high

redundancy allows the creation of a single model applying the methodology explained in section

3, that finally is converted in to a valid CAD model of the building for the subsequent analysis.

An average value of XXXX with a standar deviaton of XXXX was found in the coarse

registration process. Later, in the fine registration process this values down to XXXX with a

standard deviation of XXXX. The final hybrid point cloud had a total of 40359060 points (that

represents a 10% of the original set).

4.3. Characterisation of structural pathologies

The characterization of cracks plays a fundamental role in structure monitoring in terms of

stability and safety. Traditionally such monitoring was conducted with graduated cards,

mechanical or electronic gauges, or LVDT ( linear variable differential transformer ). However,

this equipment has significant drawbacks [27]: (i) Firstly, there is a need for permanent plates,

that may become damaged or can be lost, (ii) They provide data only from certain points and

certain directions, (iii) The cracking is not directly measured; it is assumed that its activity is

correctly defined by the variation of the reference points. In addition to to this, some of these

methods strongly rely on temperature ( this is the case of electronic gauges).

Thanks to the combined use of the shown spatial-data capture techniques, it is possible not only

to obtain high density point-clouds and photorealistic textures (this is the case of UAV+SfM

system) but also high quality orthoimages in any position and on determided surfaces, thus

solving the problems described above. All supplemented with direct product georeferencing,

which makes perfectly viable to monitor the movement of the structure and the evolution of

damage that may arise.

The aforementioned methods combined with an accurate numerical model will comprise all the

necessary tools for sizing and evaluating the restoration system of the building.

The first damage inspection of the monument [6] was carried out in 1998. The inspection

indicated that the façade suffered structural damages, made evident by cracks running from its

bottom, in the keystone to the coronation. In addition, patologies are observed in the entrance

dome keystone under the choir, in the arcs are that make up different bays of the main nave and

in cracks on the side of the building.

It is on the main facade where the building shows a greater amount of these pathological

conditions, spread along as cracking and displacement on elements of arches and vaults (Fig.8).

Fig. 8. Results of the inspection for damages: Plan view at ground level (Left). Main façade

orthoimage inspection for damages (Right).

4.4. Geometrical CAD model

Made by the proposed methodology, the Saint Torcato CAD model has greater geometric

complexity than the one exposed by Lourenço and Ramos[6]. Within this geometric

improvement is remarkable a better characterization of the main façade and towers, including

architectural details over the balcony and along the towers.

Since most of the façade shows structural pathological conditions, it is therefore expected that

the dynamic response of the structure will be influenced in part by such cracking. The high

correlation between the CAD model and the actual photogrammetric point cloud allows to

incorporate these characteristics into the CAD model directly, only requiring the meshing of the

area under study. Also this model, presents different wall tickness, increasing the model realism.

(Fig. 9).

Fig. 9. Isometrics views of the initial geometric model (Left) and the one generated by the

proposed methodology (Right).

4.5. Definition of the numerical calculation model

While the geometric aspect has been completely improved by the methodology presented, the

material characterizatión(homogeneus and isotropic), since at the time no experimental test were

carried out, the input loads and boundary conditions remain the same than the initial one. For

the loads have been consider: (i) Gravitational loads; (ii) Truss self-weight and (iii) Roof self-

weight.

Complementary to this loads conditions, it is necessary to correctly simulate the elastic

behaviour (Winkler model) of the ground in which the structure stands and also a proper

simulation of the behaviour of the tanscept. Such behaviour has been emulated through

CONTACT173/TARGET170 elements [40].

The discretization of the model has been carried out considering a 4-node isoparametric

tetrahedral element (SOLID65) with a maximum size of 0.60 m. In order to increase the

robustness of the tetrahedral mesh, element softening has been carried out using Laplace

algorithm [40].

All this results in a total of 218244 discrete elements into the numerical model (212537

SOLID65, 5707 CONTACT173 /TARGET170) (Fig.10).

Fig. 10. Isometric view of the mesh model (Left). Mesh detail of the balcony and chapels

(Right).

4.6. Modal analysis, calibration of the numerical model

The next step required to obtain an accurate finite element model is to calibrate their elastic

parameters and thus adapt the dynamic behaviour of the numerical model to the real one.In

order to accurately calibrate the numerical model it is necessary to follow a three-step

procedure: (i) Initial hypothesis, (ii) Manual calibration and (iii) Robust calibration. The initial

hypothesis considered were: the elastic propierties of masonry, the major cracks on the main

façade and the main nave, the elastic behaviour of the soil, and the simulation of the connection

between the nave and the transcept.

Within the manual calibration stage, numerous tests have been required, evaluating separately

each of the considered elastic variables and rejecting those that did not bring improvements to

the numerical model. Finally, have been chosen a total of eight parameters, namely: Young

modulu´s of the masonry (EMASONRY) and its density (δMASONRY),the normal (KNFAÇADE) and shear

(KTFAÇADE) stiffness of the major cracks on the main façade,the normal (KNFIRSTCAP) stiffness of

the major cracks on the main nave, the soil´s normal stiffness (KNSOIL), as well as the simulation

of the connection between the main nave and the transcept through a normal stiffness

(KNTRANSCEPT) and a shear one (KTTRANSCEPT). During the last step, the accurate calibration of the

previously discretized parameters through DR methodology (described above) was required,

providing the results presented below (Table 3).

Table 3: Summary of the adopted values for the calibration of the numerical model.

The now calibrated elastic properties of the masonry show a globally damaged material. The

high elasticity obtained in the simulation of the transept confirmed that the building, as it

progressed, suffered settlements and cracking. However, the rise in rigidity of the elastic

properties in comparison to the initially calculated in [6], denote soil compaction.As shown in

(Fig. 10) (Fig. 11), the relative ratios between the experimental and numerical frequencies, with

Initial values Lower bound Upper bound Updated value

EMASONRY (GPa) 10 5 15 9,19

δMASONRY (Kg/m3) 2500 2400 2700 2600

KNFAÇADE (GPa/m) 0.0001 0.00005 0.01 0.0004

KTFAÇADE (GPa/m) 0.1 0.05 1 0.53

KNFIRSTCAP (GPa/m) 1 0.05 5 0.40

KNSOIL (GPa/m) 0.585 0.0585 5.85 0.627

KNTRANSCEPT (GPa/m) 0.1 0.005 1 0.29

KTRANSCEPT (GPa/m) 0.0001 0.00001 0.01 0.00002

a value close to one for the standard MAC indexes denote a high correlation between the

experimental dynamic behaviour of the building and the numerical one. Through the simulation

of the cracks, it was possible to correctly simulate the dynamic behaviour and the high existing

elasticity in the central area of the building.

Fig. 10. Comparison between representative values of dynamic response (frequencies and

MAC): Value ratio of the initial model proposed by Lourenço (Left). Ratios obtained with the

hereby proposed methodology (Right).

Fig. 11. Comparison between the vibrational model from the OMA and those from the hereby

presented finite element numerical model.

5. Conclusions

The methodology presented aims to compile the information from different sensors in order to

establish a complete geometric characterization of historic buildings. The combined method for

data acquisition solves most common problems encountered today like the preparation of

accurate CAD models and the analysis of structure characteristics (displacements and cracking).

Using the laser scanner alone would not solve some of the problems that arise today, i.e. the

lack of data in areas that are not accessible to the system or the difficulty of cracking

identification. That is why it is essential to incorporate a complementary data capture system

able to meet solving problems. The perfect complement for an accurate, quick and complete

data capture is the Image Structure from Motion System on UAV platform. Other advantages

provided by this second capture system, lies in the potential that digital image analysis gives to

the graphical product. This digital image analysis makes possible to completely characterize

cracking (length and opening).

The binomial SfM-laser scanner is a reliable foundation from which to analyze appropriate

restoration actions, following the procedure: (i) analysis of the causes through the numerical

model (ii) displacement and stress state along the structure (iii) analysis of the effectiveness of

the system (analysis of the numerical model including restoration activities, analysis of cracks

and collapses systems).

The methodology presented can be applied to other infrastructures, such as tunnels or bridges,

given the high versatility of the sensors described and the wide range of possibilities that they

offer. All this is complemented by a global dynamic analysis of the structure that allows a

reliable calibration of the numerical model through the elastic system variables.

The Saint Torcato Church (Guimarães, Portugal) represents an ideal case study for evaluating

the potential of the method developed. Based on the geometric characterization performed

through the presented methodology, several research works are taking place, in order to improve

the characterization of the different materials by Ground Penetration Radar and Boroscopic

Camera, for further FEM analysis.

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